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The impact of spontaneous cortical activity on neural oscillations and behavioral performance: Evidence from high-definition tDCS and MEG

$839,433RF1FY2018MHNIH

University Of Nebraska Medical Center, Omaha NE

Investigators

Linked publications, trials & patents

Abstract

Project Summary/Abstract This proposal responds to RFA-MH-17-245, which requests applications focusing on the mechanisms and dose- response relationships of noninvasive neuromodulatory methods. To be considered responsive to this BRAIN Initiative related call, applicants must deliver noninvasive stimulation to a specific anatomical target(s) and/or circuit, and be able to precisely measure the effect of dose on neural activity within the target. In this project, we alter spontaneous cortical rhythms within visual attention circuitry using high-definition transcranial direct-current stimulation (tDCS), and quantify outcomes in terms of neural oscillations and behavioral performance utilizing a dynamic functional mapping approach based on magnetoencephalographic (MEG) imaging. Briefly, even in the absence of endogenous and exogenous inputs, neurons in the human cerebral cortex are known to exhibit spontaneous discharges and fluctuations in dendritic currents, as well as other electrical field activity. These neural phenomena locally summate and give rise to population-level rhythms often referred to as ?spontaneous activity,? which is ubiquitous across the human brain. While the pervasiveness of these rhythms is well known, their impact on the neural oscillations that serve cognition and underlie behavioral performance remains largely unknown. Herein, we propose and test a predictive model whereby the power of spontaneous activity adaptively regulates the dynamic range of a neural population, and that this governs the strength of oscillations within the population and thereby behavioral performance in real time. Our Aims are based upon extensive preliminary data emerging from two convergent research themes within our laboratory, and in this project we fully integrate these two areas to elucidate the basic tenets of circuit function during visual attention processing. Specifically, in Aim 1, we investigate a large group of young adults and use MEG to quantify how the power of pre-stimulus spontaneous activity, at distinct frequencies, governs the strength of oscillatory responses at the same frequency within a given neural population, and in-turn how this oscillatory amplitude dictates behavioral performance. In Aim 2, we systematically modulate local spontaneous activity within discrete frequency bands by applying high- definition tDCS to the visual cortex of the same young adults from Aim 1. Based on extensive preliminary data, this will enable us to both increase and decrease spontaneous power at targeted frequencies within these neural populations, and then quantify the effect of these manipulations on oscillatory responses to, and subsequent performance on, visual attention tasks. Finally, in Aim 3, we will enroll a large group of older adults who are known to exhibit naturally-elevated spontaneous activity, apply tDCS to modulate such activity, and then again measure the outcomes in terms of behavioral performance and oscillatory amplitude. Together, these methodologically-integrated experiments will provide pivotal insights into how tDCS quantitatively affects cortical physiology and, in turn, clarify the mechanisms by which human neural circuits incorporate pre-stimulus ?spontaneous? activity states with stimulus-related information within discrete networks.

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